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At least 55 records · Page 3

Validation of URANS and STRUCT-ε turbulence models for stratified sodium flow

Simulations of a transient stratified sodium experiment are carried out using a classic unsteady RANS model and the second-generation URANS model, STRUCT-ε. Turbulence modeling challenges and their implications to stratified flow prediction are discussed in the context of other sources of error. Input errors are discussed and addressed; discretization error is calculated to be less than 5% of the inlet velocity, for 80% of the domain; and remaining errors in temperature distributions are attributed to the turbulence model. Qualitative flow features from the simulations are presented and discussed. Compared to the experiment, the STRUCT-ε turbulence model provides a more physically accurate prediction of temperature and momentum mixing in key regions of the domain. Quantitative measures such as the L 2 norm of the temperature discrepancy demonstrate the improved performance of the STRUCT-ε approach. In conclusion, the magnitude of the temperature fluctuations is very well-predicted by the STRUCT-ε, while URANS overpredicts them by approximately 50%.

42 ENGINEERING↗

Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

Abstract The regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

58 GEOSCIENCES↗

Relating flow resistance to equivalent roughness

Describing flow resistance using the physical properties of an underlying surface is a recalcitrant problem in overland flow models. If discharge measurements are available, an equivalent roughness (e.g., Manning’s n) can be calibrated to represent the effects of surface properties within the domain with a single numerical value. Alternatively, the flow resistance can be estimated from discharge and velocity measured at a point, typically a runoff plot outlet. However, such experimental estimates are often inconsistent with the equivalent roughness determined from calibration to discharge, even if both derive from the same dataset. For example, if Manning’s equation is used to parameterize flow resistance, the Manning’s n obtained by calibrating a model to discharge differs from the value of n calculated from measured flow and velocity at the hillslope outlet. Here, this discrepancy is resolved by deriving a correction factor relating experimentally-determined flow resistance to the equivalent roughness. The derived correction factor is tested for four commonly-used resistance formulations using 129 rainfall simulator experiments. The correction factor is necessary to reproduce measured velocities, and yields minor improvements in discharge prediction. Plain Language Summary: Accurate runoff prediction is needed for land and water management in dryland regions, where sporadic and limited rainfall necessitate efficient water use and drought mitigation strategies. The skill of runoff models is known to be hindered by out ability to estimate flow resistance, which is the quantity that describes how energy is lost from flowing water to the underlying surface. Typically, models represent flow resistance with an equivalent roughness, e.g., Manning’s n, that is adjusted until the model can reproduce available discharge observations at watershed scale. However, the flow resistance measured in plot-scale experiments (1–10 m) often exceeds equivalent roughness coefficients by a factor of 10. This means that the direct use of plot-scale experimental data to parameterize runoff models could cause errors in discharge and runoff velocity predictions. Here, we resolve these differences by deriving an analytic correction factor that relates flow resistance to the equivalent roughness required for models to reproduce experimental velocity and discharge data. This correction factor is tested using rainfall simulator data from 129 experiments performed in the US Southwest covering a wide range of precipitation intensities, soil textures and vegetation types. Use of the correction factor substantially improves model prediction of flow velocity, which is needed for reproducing the timing of flood events and the estimation of erosion.

54 ENVIRONMENTAL SCIENCES↗

X-ray sources for in situ wavelength calibration of x-ray imaging crystal spectrometers

X-ray sources for a range of wavelengths are being considered for in situ calibration of X-ray Imaging Crystal Spectrometers (XICSs) and for monitoring line shifts due to changes in the crystal temperature, which can vary during experimental operation over a day [A. Ince-Cushman et al., Rev. Sci. Instrum. 79, 10E302 (2008), L. Delgado-Aparicio et al., Plasma Phys. Control. Fusion 55, 125011 (2013)]. Such crystal temperature dependent shifts, if not accounted for, could be erroneously interpreted as Doppler shifts leading to errors in plasma flow-velocity measurements. The x-ray sources encompass characteristic x-ray lines falling within the wavelength range of 0.9–4.0 Å, relevant for the XICSs on present and future fusion devices. Several technological challenges associated with the development of x-ray sources for in situ calibration are identified and are being addressed in the design of multiple x-ray tubes, which will be installed inside the spectrometer housing of the XICS for the JT-60SA tokamak. These x-ray sources will be especially useful for in situ calibration between plasma discharges. Here, in this paper, laboratory experiments are described that were conducted with a Cu x-ray source, a heated quartz (102) crystal, and a pixelated Pilatus detector to measure the temperature dependent shifts of the Cu Kα 1 and Kα 2 lines at 1.5405 and 1.5443 Å, respectively, and to evaluate the 2d-lattice constant for the Bragg reflecting crystal planes as a function of temperature, which, in the case of in situ wavelength calibration, would have to be used for numerical analysis of the x-ray spectra from the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A fast, matrix-based method to perform omnidirectional pressure integration

Abstract Experimentally-measured pressure fields play an important role in understanding many fluid dynamics problems. Unfortunately, pressure fields are difficult to measure directly with non-invasive, spatially resolved diagnostics, and calculations of pressure from velocity have proven sensitive to error in the data. Omnidirectional line integration methods are usually more accurate and robust to these effects as compared to implicit Poisson equations, but have seen slower uptake due to the higher computational and memory costs, particularly in 3D domains. This paper demonstrates how omnidirectional line integration approaches can be converted to a matrix inversion problem. This novel formulation uses an iterative approach so that the boundary conditions are updated each step, preserving the convergence behavior of omnidirectional schemes while also keeping the computational efficiency of Poisson solvers. This method is implemented in Matlab and also as a GPU-accelerated code in CUDA-C++. The behavior of the new method is demonstrated on 2D and 3D synthetic and experimental data. Three-dimensional grid sizes of up to 125 million grid points are tractable with this method, opening exciting opportunities to perform volumetric pressure field estimation from 3D PIV measurements.

42 ENGINEERING↗

Coincidence Anticipation Timing Responses with Head Tracking and Eye Tracking

Head tracking movements are common in interceptive tasks. The benefits of these movements are unclear. The purpose of this study was to compare coincidence anticipation timing (CAT) responses for a simulated approaching object when the eyes were used in tracking the object and when the head was used in tracking the object.A total of 29 subjects participated. A Bassin Anticipation Timer consisting of a track of sequentially illuminated lights was used to simulate an approaching object at velocities of 223 cm · s -1 to 894 cm · s -1 . Each velocity was used 10 times under 2 conditions. In one condition, subjects were told to turn the eyes with the stimulus. In the other condition, subjects viewed the stimulus through apertures and were told to turn the head with the stimulus. Subjects pushed a button to coincide with illumination of the final light on the track. Signed CAT errors, unsigned CAT errors, and variable CAT errors were compared between the head movement (HM) and eye movement (EM) conditions. No significant differences were noted for the signed errors (mean signed error at 894 cm · s -1 ; 10.3 ± 75.4 ms (HM), -16.1 ± 51.0 ms (EM). However, the unsigned and variable errors were significantly larger at some stimulus velocities in the head movement condition [mean unsigned error at 894 cm · s -1 : 82.6.0 ± 45.9 ms (HM), 59.0 ± 22.4 ms (EM); mean variable error at 894 cm · s -1 ; 78.0 ± 37.8 ms (HM), 49.2 ± 17.1ms (EM)]. DISCUSSION: Head movement did not result in improved CAT performance compared to eye movements. Further work will be required to determine whether these results are generalizable to situations where head tracking is required but apertures are not worn.

Biophysics↗

Heterogeneous mantle effects on the behavior of SmKS waves and outermost core imaging

Seismic traveltime anomalies of waves that traverse the uppermost 100–200 km of the outer core have been interpreted as evidence of reduced seismic velocities (relative to radial reference models) just below the core–mantle boundary (CMB). These studies typically investigate differential traveltimes of SmKS waves, which propagate as P waves through the shallowest outer core and reflect from the underside of the CMB m times. The use of SmKS and S(m-1)KS differential traveltimes for core imaging are often assumed to suppress contributions from earthquake location errors and unknown and unmodelled seismic velocity heterogeneity in the mantle. The goal of this study is to understand the extent to which differential SmKS traveltimes are, in fact, affected by anomalous mantle structure, potentially including both velocity heterogeneity and anisotropy. Velocity variations affect not only a wave's traveltime, but also the path of a wave, which can be observed in deviations of the wave's incoming direction. Since radial velocity variations in the outer core will only minimally affect the wave path, in contrast to other potential effects, measuring the incoming direction of SmKS waves provides an additional diagnostic as to the origin of traveltime anomalies. Here we use arrays of seismometers to measure traveltime and direction anomalies of SmKS waves that sample the uppermost outer core. We form subarrays of EarthScope's regional Transportable Array stations, thus measuring local variations in traveltime and direction. We observe systematic lateral variations in both traveltime and incoming wave direction, which cannot be explained by changes to the radial seismic velocity profile of the outer core. Moreover, we find a correlation between incoming wave direction and traveltime anomaly, suggesting that observed traveltime anomalies may be caused, at least in part, by changes to the wave path and not solely by perturbations in outer core velocity. Modelling of 1-D ray and 3-D wave propagation in global 3-D tomographic models of mantle velocity anomalies match the trend of the observed traveltime anomalies. Overall, we demonstrate that observed SmKS traveltime anomalies may have a significant contribution from 3-D mantle structure, and not solely from outer core structure.

58 GEOSCIENCES↗

Heterogeneous mantle effects on the behavior of SmKS waves and outermost core imaging

Seismic traveltime anomalies of waves that traverse the uppermost 100–200 km of the outer core have been interpreted as evidence of reduced seismic velocities (relative to radial reference models) just below the core–mantle boundary (CMB). These studies typically investigate differential traveltimes of SmKS waves, which propagate as P waves through the shallowest outer core and reflect from the underside of the CMB m times. The use of SmKS and S(m- 1)KS differential traveltimes for core imaging are often assumed to suppress contributions from earthquake location errors and unknown and unmodelled seismic velocity heterogeneity in the mantle. The goal of this study is to understand the extent to which differential SmKS traveltimes are, in fact, affected by anomalous mantle structure, potentially including both velocity heterogeneity and anisotropy. Velocity variations affect not only a wave’s traveltime, but also the path of a wave, which can be observed in deviations of the wave’s incoming direction. Since radial velocity variations in the outer core will only minimally affect the wave path, in contrast to other potential effects, measuring the incoming direction of SmKS waves provides an additional diagnostic as to the origin of traveltime anomalies. Here we use arrays of seismometers to measure traveltime and direction anomalies of SmKS waves that sample the uppermost outer core. We form subarrays of EarthScope’s regional Transportable Array stations, thus measuring local variations in traveltime and direction. We observe systematic lateral variations in both traveltime and incoming wave direction, which cannot be explained by changes to the radial seismic velocity profile of the outer core. Moreover, we find a correlation between incoming wave direction and traveltime anomaly, suggesting that observed traveltime anomalies may be caused, at least in part, by changes to the wave path and not solely by perturbations in outer core velocity. Modelling of 1-D ray and 3-D wave propagation in global 3-D tomographic models of mantle velocity anomalies match the trend of the observed traveltime anomalies. Overall, we demonstrate that observed SmKS traveltime anomalies may have a significant contribution from 3-D mantle structure, and not solely from outer core structure.

58 GEOSCIENCES↗

Code for paper "Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces"

New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.

Grosskopf, Michael↗

Automatic Échelle Spectrograph Wavelength Calibration

Time-domain astronomy and the increasing number of exoplanet candidates call for reliable, robust, and automatic wavelength calibration. We present an algorithm for wavelength-calibrating échelle spectrographs that uses order-by-order extracted spectra and a list of laboratory wavelengths. Our approach is fully automatic and does not need the pixel locations of certain spectral features with which to anchor the wavelength solution, nor the true order number of each diffraction order. We use spectral features that are duplicated in adjacent orders to establish the scale-invariant component of the wavelength solution. We then match the central wavelengths of spectral features to laboratory wavelengths to establish the scale and higher-order components of the wavelength solution. We demonstrate our method on the four spectrographs of Las Cumbres Observatory’s Network of Robotic Échelle Spectrographs (NRES), on the High Accuracy Radial Velocity Planet Searcher (HARPS) spectrograph, and on synthetic data. We obtain a velocity-equivalent precision of ∼10 m s{sup −1} on NRES. We achieve ∼1 m s{sup −1} on HARPS, which agrees with the precision reported by the HARPS team. On synthetic data, we achieve the velocity precision set by Gaussian centroiding errors. Our algorithm likely holds for a wide range of spectrographs beyond the five presented here. We provide an open-source Python package, xwavecal, which outputs wavelength-calibrated spectra as well as the wavelengths of spectral features.

79 ASTRONOMY AND ASTROPHYSICS↗

Ion temperature measurements from tomographic reconstruction of Doppler spectra in the presence of multi-component flow in two dimensions

A new ion Doppler diagnostic has been constructed to measure ion temperature profiles in the presence of multi-component flow during magnetic reconnection experiments. The inversion technique and diagnostic setup are applicable to axisymmetric plasmas with two-component flow across the measurement cross section, which occurs during magnetic reconnection. The particular design discussed here is optimized for operation on the Magnetic Reconnection eXperiment (MRX) at Princeton Plasma Physics Laboratory. To prove the viability of this diagnostic for MRX and the future Facility for Laboratory Reconnection Experiments, measurements have been taken and ion temperature and perpendicular flow profiles have been obtained. The radial velocity on MRX does not contribute to the Doppler shift of the measured spectra but does contribute to the broadening of the spectra, while toroidal flow contributes to both. It is shown that neglecting the radial velocity for vR = 20 km/s leads to an error in the ion temperature inversion of 20%. Results from MRX discharges are shown, and the impact of radial velocity on ion temperature inversions is discussed.

Goodman, A. (ORCID:0000000336396572)↗

Quantifying wind plant blockage under stable atmospheric conditions

Wind plant blockage reduces the wind velocity upstream undermining turbine performance for the first row of the plant. We assess how atmospheric stability modifies the induction zone of a wind plant in flat terrain. We also explore different approaches to quantifying the magnitude and extent of the induction zone from field-like observations. To investigate the influence from atmospheric stability, we compare simulations of two stable boundary layers using the Weather Research and Forecasting model in large-eddy simulation mode, representing wind turbines using the generalized actuator disk approach. We find a faster cooling rate at the surface, which produces a stronger stably stratified boundary layer, amplifies the induction zone of both an isolated turbine and of a large wind plant. A statistical analysis on the hub-height wind speed field shows wind slowdowns only extend far upstream (up to 15D) of a wind plant in strong stable boundary layers. To evaluate different ways of measuring wind plant blockage from field-like observations, we consider various ways of estimating the freestream velocity upstream of the plant. Sampling a large area upstream is the most accurate approach to estimating the freestream conditions, and thus of measuring the blockage effect. Also, the choice of sampling method may induce errors of the same order as the velocity deficit in the induction zone.

54 ENVIRONMENTAL SCIENCES↗

Assessment of Crustal Leg Uncertainties for RSTT Path-dependent Uncertainty

The Regional Seismic Travel Time (RSTT) model and software were recently updated to allow for path-dependent uncertainty (PDU) estimates for travel-time (Begnaud et al. 2021; Begnaud et al. 2020). Begnaud et al. (2021) describes the process of improving the current distance-dependent uncertainty parameterization for RSTT using a random effects model (REM) to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The REM separates the error between observed slowness and model predicted slowness into bias and random components. The PDU is calculated by integrating these mean squared errors along a seismic-phase ray path.

58 GEOSCIENCES↗

A Tidal Hydrodynamic Model for Cook Inlet, Alaska, to Support Tidal Energy Resource Characterization

Cook Inlet in Alaska has been identified as a prime site in the U.S. for potential tidal energy development, because of its enormous tidal power potential that accounts for nearly one-third of the national total. As one important step to facilitate tidal energy development, a tidal hydrodynamic model based on the unstructured-grid, finite-volume community ocean model (FVCOM) was developed for Cook Inlet to characterize the tidal stream energy resource. The model has a grid resolution that varies from about 1000 m at the open boundary to 100–300 m inside the Inlet. Extensive model validation was achieved by comparing model predictions with field observations for tidal elevation and velocity at various locations in Cook Inlet. The error statistics confirmed the model performs reasonably well in capturing the tidal dynamics in the system, e.g., R2 > 0.98 for tidal elevation and generally > 0.9 for velocity. Model results suggest that tides in Cook Inlet evolve from progressive waves at the entrance to standing waves at the upper Inlet, and that semi-diurnal tidal constituents are amplified more rapidly than diurnal constituents. The model output was used to identify hotspots that have high energy potential and warrant additional velocity and turbulence measurements such as East Foreland, where averaged power density exceeds 5 kw/m2. Lastly, a tidal energy extraction simulation was conducted for a hypothetical turbine farm configuration at the Forelands cross section to evaluate tidal energy extraction and resulting changes in far-field hydrodynamics.

16 TIDAL AND WAVE POWER↗

Model-predictive optimal control of ferrofluidic microrobots in three-dimensional space

Ferrofluid microrobots have emerged as promising tools for minimally invasive medical procedures. Their unique properties to navigate complex fluids and reach otherwise inaccessible regions of the human body have enabled new applications in targeted drug delivery, tissue engineering, and diagnostics. Here, this paper proposes a model-predictive controller for the external magnetic manipulation of ferrofluid microrobots in three dimensions (3D). The internal optimization routine of the controller determines appropriate changes in the applied electromagnetic field to minimize the deviation between the actual and desired trajectories of the microrobot. A linear system governing locomotion is derived and used as the equality constraints of the optimization problems associated with the feedback index. In addition to ferrofluid droplets, the controller presented in this work may be applied to other magnetically-pulled microrobots. Several experiments are performed to validate the controller and showcase its ability to adapt to changes in system parameters such as the desired tracking trajectory and the size, orientation, deformation, and velocity of the microrobot. The accuracy of the controller is analyzed for each experiment, and the average error is found to be within 0.25 mm for small velocities. An additional experiment is performed to demonstrate significant improvement over a PID controller that is optimally tuned using Bayesian optimization. The results presented in this paper suggest that the proposed control algorithm could enable new microrobotic capabilities in minimally invasive medical procedures, lab-on-a-chip applications, and microfluidics.

60 APPLIED LIFE SCIENCES↗

Artificial intelligence models, photos, and data associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” (v2)

This data package is associated with the manuscript “Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO” published in Water Resources Research (Chen et al., 2024). This data package includes the training, validation, testing, and prediction data used by the artificial intelligence (AI) model for automated grain size and hydro-biogeochemistry quantification using streambed photos. The grain size data are extracted for each photo using You Look Only Once (YOLO), a pre-trained object detection model. This data package was originally published in October 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. Please see flmd.csv for a list of all files contained in this data package and descriptions for each. Please see dd.csv for a data dictionary that defines the column headers of .csv files in the data package. This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; and (4) six subfolders. Subfolders 1 to 4 include the training, validation, testing, and prediction data. Subfolder 5_Summary includes the summary results of different combinations of training, validation, testing, and prediction data. Subfolder 6_SupplementalData includes additional data downloaded from public sources (Kaufman et al., 2023a; Kaufman et al., 2023b; Garefalakis et al., 2023; Mair et al., 2024; https://github.com/river-corridors-sfa/Geospatial_variables). In total, the data package includes 110 folders and 44,283 files. These files include 9,047 .jpg photos, 1 .png photo, 3 .tif photos; 26,639 photo labels and individual grain sizes and probability from AI (.txt); 8,447 grain size distribution data (.dat); and 126 CSV files for results summary, and 14 required metadata files (.xlsx). The summary CSV files contain 68 columns and approximately 2,200 rows that represent photo names, site locations, recording time, GPS coordinates, grains sizes (D10, D50, D60, and D84), number of grains, and additional hydro-biogeochemical data such as water depth, flow velocity, Manning’s coefficient, friction factor, hydraulic conductivity, permeability, streambed interstitial velocity magnitude, mass transfer rate, and nitrate uptake velocity. The photos were obtained from 75 sites in the Yakima River Basin and the Columbia River shorelines, and other associated data from samples and sensors obtained when the photos were taken are publicly available (Fulton et al. 2022; Grieger et al. 2023). All files are .csv, .txt, .dat, .jpg, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Forward modeling of Doppler velocity interferometer system for improved shockwave measurements

We report that when near-instantaneous shocks are recorded by using a Doppler velocity interferometer velocity interferometer system for any reflector (VISAR), they typically exceed the detector’s ability to react and “skipped fringes” result, where its visibility briefly reduces. Traditionally, replacing skipped fringes required guesswork in analysis, which increased arrival time errors. Second, the use of long but velocity-sensitive interferometer delays with fast detectors which can resolve the delay has traditionally been avoided because of the fear of confusing the arrival time signal. However, shorter delays produce smaller fringe phase shifts per velocity and, thus, can decrease velocity precision. We realize that while some loss of fringe information occurs at shock events, this is often just a partial loss and the residual fringe information can still hold valuable information. We describe a forward model (FM) of the interferometer action and detector blurring that assists with VISAR fringe analysis at skipping events: (1) more precise shock arrival times, (2) arrival time precision not limited by long delays, and (3) improved ghost subtraction, which improves accuracy over a broad time region. Lastly, we demonstrate the utility of a FM on National Ignition Facility and Laboratory for Laser Energetics Omega shots and discuss data process methods to increase the high time resolution of VISAR systems despite their limitations and complexities.

47 OTHER INSTRUMENTATION↗

Free space Thomson scattering to study high energy density shocks

A free space collective Thomson scattering system has been developed to study pulsed power produced plasmas. While most Thomson scattering diagnostics on pulsed power machines use a bundle of fibers to couple scattered light from the plasma to the spectrometer, this system used free space coupling of the light, which enabled a spatially continuous image of the plasma. Initial experiments with this diagnostic were performed on an inverse wire array generated by a 200 kA, 1100 ns rise time pulse power generator. The capabilities of this diagnostic were demonstrated by using the low frequency ion acoustic wave feature of the Thomson scattering spectra to measure the plasma flow velocity. The diagnostic was demonstrated to measure velocities between 20 and 40 km/s with an error of 4.7 km/s when fitting with a 600 μm spatial resolution or 8.9 km/s when fitting with a 150 μm spatial resolution. In some experiments, the diagnostic observed a bow shock in the plasma flow as the scattering intensity increased and flow velocity decreased.

47 OTHER INSTRUMENTATION↗